The eighth edition of The Fifth Elephant will be held in Bangalore on 25 and 26 July. A thousand data scientists, ML engineers, data engineers and analysts will gather at the NIMHANS Convention Centre in Bangalore to discuss:
- Model management, including data cleaning, instrumentation and productionizing data science.
- Bad data and case studies of failure in building data products.
- Identifying and handling fraud + data security at scale
- Applications of data science in agriculture, media and marketing, supply chain, geo-location, SaaS and e-commerce.
- Feature engineering and ML platforms.
- What it takes to create data-driven cultures in organizations of different scales.
1. Meet Peter Wang, co-founder of Anaconda Inc, and learn about why data privacy is the first step towards robust data management; the journey of building Anaconda; and Anaconda in enterprise.
2. Talk to the Fulfillment and Supply Group (FSG) team from Flipkart, and learn about their work with platform engineering where ground truths are the source of data.
3. Attend tutorials on Deep Learning with RedisAI; TransmorgifyAI, Salesforce’s open source AutoML.
4. Discuss interesting problems to solve with data science in agriculture, SaaS perspective on multi-tenancy in Machine Learning (with the Freshworks team), bias in intent classification and recommendations.
5. Meet data science, data engineering and product teams from sponsoring companies to understand how they are handling data and leveraging intelligence from data to solve interesting problems.
Why you should attend?
- Network with peers and practitioners from the data ecosystem
- Share approaches to solving expensive problems such as cleanliness of training data, model management and versioning data
- Demo your ideas in the demo session
- Join Birds of Feather (BOF) sessions to have productive discussions on focussed topics. Or, start your own Birds of Feather (BOF) session.
Full schedule published here: https://hasgeek.com/fifthelephant/2019/schedule
For more information about The Fifth Elephant, sponsorships, or any other information call +91-7676332020 or email firstname.lastname@example.org
JSFoo:VueDay 2019 sponsors:
[BoF] Tackling the complex inter-dependent challenges in transport planning and assignment
Session type: Birds of a Feather session of 1 hour Session type: BOF session of 1 hour
Topics to be discussed:
- Variations in the planning/assignment problem formulation and scope.
- Understanding the interplay of multiple objectives- minimizing SLA/service-time breaches, increasing the efficiency of the system, dealing with worst-case scenarios, heterogeneity of the region/occasion where and when it is deployed.
- Landscape of the theoretical approaches ( eg., solutions using integer linear programming, dynamic programming, NP-complete strategies such as branch-and-bound, computational heuristics, GA/simulated-annealing/tabu-seach, any well-known approximation/asymptotic results ).
- Dealing with erroneous/inaccurate predictions.
As the focus here is on the technical discussion, the drivers would ideally be the ones who’ve worked on designing the automated system for shipment delivery/route optimization and/or implementing the solution in the real-world.
Key takeaways from this session
Learning about the preferred tools and techniques that are being employed to solve routing problems. Is there such a thing as state-of-the-art in this case? Understanding the similarities and differences in problem formulation, issues and performance across the different businesses/firms. Where is the greatest scope for improvement? Who can bring fresh insights in this area?
Anyone interested in technical aspects of logistics problems/optimization or learning about the significant challenges involved in arriving at a desirable solution. People curious about how everything from cab aggregators to food delivery to ecommerce shipment scheduling works in the background.
What this session will not be about
Although the discussion is not intended to go deep into algorithmic details, anyone who strictly wants to avoid technical discussions (for example, understanding trade-off between algorithmic performance and computational complexity) may want to skip it. Also, if people are not particularly interested in optimization problems, then they might want to skip it too unless they are otherwise really interested in the domain.
- Venkateshan K (Flipkart)
- Vaibhav Khandelwal (Shadowfax)
- Jayaram Kasi (Pikkol)
- Rahul Jain (Locus)